A variety of signal sampling techniques are known. Traditional uniform sampling techniques often limit the maximum frequency of the signal that can be recovered due to the Nyquist limit and the effect of aliasing caused by slow sampling. Techniques to defeat aliasing fall into two general categories: multiple uniform sampling techniques and non-uniform sampling techniques. There are also some hybrid techniques that have been used, such as those that use non-uniform modulation of the signal followed by uniform sampling, in an attempt to overcome the Nyquist limit and to find ways to combat the effects of aliasing. However, these techniques often require substantial hardware or computing resources to recover signals of interest in a wideband application. The resources needed to extract a signal of interest typically grow rapidly as the frequency spectrum of interest widens.
In the area of extremely wideband receivers, there is yet another class of problems that arises when looking for weaker signals in the presence of stronger signals. These problems get compounded when the weaker signals can occur anywhere within an extremely broad spectrum and are mixed with strong signals of interest. In addition, the application environment is often constrained by the availability of hardware and computing resources.